Machine Learning in Production
Completed by Binay Rawat
February 11, 2026
11 hours (approximately)
Binay Rawat's account is verified. Coursera certifies their successful completion of Machine Learning in Production
What you will learn
Identify key components of the ML project lifecycle, pipeline & select the best deployment & monitoring patterns for different production scenarios.
Optimize model performance and metrics by prioritizing disproportionately important examples that represent key slices of a dataset.
Solve production challenges regarding structured, unstructured, small, and big data, how label consistency is essential, and how you can improve it.
Skills you will gain
- Category: Application Deployment
- Category: Data Maintenance
- Category: MLOps (Machine Learning Operations)
- Category: Continuous Deployment
- Category: Applied Machine Learning
- Category: Data Synthesis
- Category: Data Validation
- Category: Data Preprocessing
- Category: Data Collection
- Category: Model Training
- Category: Data Integrity
- Category: Model Deployment
